Banggai cardinalfish ([i]Pterapogon kauderni[i]) populations (stocks ...

1

Banggai cardinalfish (Pterapogon kauderni) populations (stocks) around Banggai Island, 1

a geometric and classical morphometric approach 2

Samliok Ndobe1

and Abigail Moore2 3

1 Faculty of Animal Husbandry and Fisheries, Tadulako University, Palu, Central Sulawesi, 4

Indonesia. Email: [email protected] 5

2 Sekolah Tinggi Perikanan dan Kelautan (STPL), Palu, Central Sulawesi, Indonesia. Email: 6

[email protected]

7

Corresponding author: Abigail M. Moore 8

Postal Address: Sekolah Tinggi Perikanan dan Kelautan (STPL), Kampus Madani, 9

Jl Soekarno-Hatta km6, Palu 94118, Sulawesi Tengah, Indonesia 10

Telephone (office): +62 451 4709936 11

Email: [email protected] 12

ABSTRACT 13

Background. The identification and characterisation of appropriate management units 14

(stocks) is important as a basis for responsible fisheries management as well as conservation 15

of within species biodiversity. The Banggai cardinalfish Pterapogon kauderni (F.P. 16

Koumans,1933), a mouthbrooding apogonid with Endangered status (IUCN Red List) has 17

been shown to have a high level of genetic population structure across the endemic 18

distribution in the Banggai Archipelago. With a life-cycle making recovery frrm extirpation 19

extremely unlikely, this indicates a need to conserve each reproductively isolated population 20

(stock), in particular to support zonation of Banggai Island in the context of the proposed 21

district marine protected area. Genetic and morphological variations are often but not always 22

related, and ideally both should be used in stock identification. However there were no data 23

on classical or geometric morphometric characteristics of P. kauderni populations. 24

PeerJ PrePrints | http://dx.doi.org/10.7287/peerj.preprints.182v1 | CC-BY 3.0 Open Access | received: 30 Dec 2013, published: 30 Dec 2013

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Methods. Adult P. kauderni for classical and geometric morphometric analyses were 25

collected randomly at six sites on Banggai Island (31-34 adult fish/site, total 193). Eleven 26

morphometric parameters were measured and 10 dimensionless ratios were compared using 27

the ANOVA function in Microsoft Excel 2007. A landmark set for P. kauderni was 28

developed. Each specimen was photographed, digitised (tps.dig and tps.util). Characteristics 29

of the six populations were analysed using Canonical Variate Analysis (CVA) and 30

Discriminant Function Analysis (DFA) in MorphoJ geometric morphometric software to 31

identify significant between-site variation. The results were compared with genetic, 32

geophysical, bio-ecological and socio-economic data to determine meaningful stocks or 33

management units. 34

Results. Except for one site pair (Monsongan and Tinakin Laut) we found significant or 35

highly significant differences between sites (sub-populations) in morphometric 36

characteristics, as well as from the CVA and DFA results. The greatest morphometric 37

difference was between sub-populations at the north (Popisi) and southeast (Matanga) 38

extremities of the Banggai Island P. kauderni distribution. The Popisi population was 39

characterised by short/high head shape, Matanga by a more hydrodynamic shape (elongated 40

with a more pointed head). These findings were consonant with genetic study results. We 41

propose a population model with four closed populations and one metapopulation resulting in 42

five P. kauderni stocks around Banggai Island. 43

Discussion. The observed pattern of morphometric variation could be related to geographical 44

spread (radiation or North-South gradient), habitat-driven selection or growth patterns, 45

stochastic events, or a combination. Such fine-scale sub-population or stock characterisation 46

calls for intra-species conservation, with implications for the management of this restricted 47

range endemic ornamental fish not only around Banggai Island but throughout the P. 48

kauderni endemic distribution. 49


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INTRODUCTION 50

It is generally accepted that species management, including conservation measures and 51

sustainable use, should be based on biologically and ecologically meaningful units or sub-52

populations, which for fishes are generally referred to as stocks. Beg and Waldman (1999) 53

found that the term stock is somewhat ambiguous, concluding that stock definition should 54

evolve with management requirements and technological advances, and advocated a holistic 55

approach to fish stock identification based on morphometric, life history and genetic data. 56

Reiss et al.(2009) stated that "an essential prerequisite of sustainable fisheries management is 57

the matching of biologically relevant processes and management action", with fish stocks as 58

the fundamental unit, but found that fish biology and management action are commonly 59

mismatched. Waldman (2005) listed the following characteristics shared by a given stock: a 60

physical life-cycle circuit; set of demographic influences; isolation allowing fine-tuning of 61

specific morphological and genetic characteristics; and subjection to unnatural influences 62

such as fishing pressure and pollution. 63

Kritzer and Sale (2004) writing on metapopulation ecology in the sea described three 64

population structures: (A) closed local populations, with no ecologically meaningful 65

exchange of individuals, highly localized dispersal distances; (B) a metapopulation or 66

network of partially closed populations with nontrivial supply from other populations; and 67

(C) a patchy population, within which individuals are distributed among discrete groups and 68

local populations essentially draw from a common larval pool. For a given species these 69

structures could be nested at different scales or different structures could occur in different 70

environmental conditions, and the structure will greatly affect the impacts of conservation 71

measures such as marine protected areas and other fisheries management tools. It logically 72

follows that in the case of closed populations (stocks) with no meaningful exchange (gene 73

flow) between them, protection of one of these will have no impact on the status of the 74

others. Furthermore, if any one should become depleted, replenishment would be very 75

unlikely and local extinction(s) would most likely be permanent, would involve the loss of 76

any specific evolved traits and potentially of unique genetic strains and adaptations, thus 77

reducing biodiversity at an intra-species (genetic and possibly phenotypic) level. From a 78

within species biodiversity conservation viewpoint, Rocha et al., (2007) note that the front 79

line in marine conservation genetics is the identification of management units, that 80

phylogeography can assist in revealing isolated and unique lineages, and stress the 81

importance of adequate protection for each of these reproductively isolated populations or 82

stocks. Ward (2006) pointed out the importance of identifying population structure in the 83


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context of re-stocking or stock enhancement, in order to maintain population genetic 84

characteristics through appropriate broodstock selection. 85

As Hammer and Zimmermann (2005) pointed out, it has become evident that genetic 86

methods have great potential for population studies, however in stock identification they 87

considered it important that other identifiers such as specific ecology, meristic or 88

morphological traits should be congruent with genetic results, echoing the concern of Coyle 89

(1998) that several methods should be used in identifying fish stocks. Genetic and 90

morphological variations are often but not always related (Rocha et al., 2007). While a 91

literature search readily reveals growing numbers of genetic stock and population structure 92

studies, there have been relatively few morphometric studies aimed at fish stock 93

identification, most of which have concentrated on freshwater fishes (e.g. Adams et al., 2007, 94

Hossein et al., 2010), or commercially important food fishery species with wide distributions 95

(e.g. Turan, 2004), while studies where the results of genetic and morphometric analyses are 96

compared such as Cabral et al. (2003), Vasconcellos et al. (2008) or Turan and Yaglioglu 97

(2010) are still rare. 98

The Banggai cardinalfish Pterapogon kauderni (Koumans, 1933) is a marine fish of 99

conservation concern for which such concerns are particularly relevant. A paternal 100

mouthbrooding apogonid with direct development (Vagelli, 1999), the life history does not 101

include a pelagic phase. Despite a tendency to ontogenetic shift in microhabitat (Vagelli, 102

2004; Ndobe et al., 2008), the Banggai cardinalfish exhibits extreme philopatry (Kolm et al., 103

2005). The species has been shown to have a high level of genetic population structure across 104

the endemic distribution in the Banggai Archipelago, Central Sulawesi, Indonesia, with 105

genetically distinct sub-populations (arguably stocks) occurring on the same island as little as 106

2-5km apart (Bernardi and Vagelli, 2004; Hoffman et al., 2005; Vagelli et al., 2009). 107

Traded as a marine ornamental in large numbers since the 1990's (Allen, 2000; Kolm 108

and Berglund, 2003; Lunn and Moreau, 2004; Moore et al., 2011), the conservation status of 109

P. kauderni has become a national and international issue. Proposed for CITES listing in 110

2007 (Moore and Ndobe, 2007a; Indrawan and Suseno, 2008; Vagelli, 2008), P. kauderni 111

was listed with Endangered status in the IUCN Red List later in the same year (Allen and 112

Donaldson, 2007). The CITES proposal was withdrawn and Indonesia made a commitment to 113

Banggai cardinalfish conservation with a sustainable ornamental fishery approach. At the 114

District level the District head issued two decrees, establishing a Banggai Cardinalfish Centre 115

(BCFC) and a marine protected area network consisting of ten islands, two of which were 116

specifically designated for P. kauderni conservation. In fact, only one of these, Banggai 117


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Island, actually has a P. kauderni population; Togong Lantang Island has a large Sphaeramia 118

nematoptera population living among Rhizophora prop roots, which could have been 119

mistakenly identified by inexperienced observers, but no Banggai cardinalfish (Ndobe et al., 120

2012). 121

Banggai Island is the second largest island in the Banggai Archipelago, with an area of 122

around 294km2, over 37,000 inhabitants, 4 sub-districts. Of the 27 villages, at least 5 were 123

involved in the Banggai cardinalfish ornamental fishery in 2004, and two villages are still 124

active in this fishery: Bone Baru in the north of the island, arguably the most active centre of 125

the Banggai cardinalfish trade in the archipelago, and Tolokibit in the south (Moore et al., 126

2011). Bone Baru has been the focus of several government and NGO programs and has a 127

community marine protected area (MPA), coral reef and mangrove conservation groups and 128

an officially recognised ornamental fishers group. Pterapogon kauderni populations are 129

distributed around the northern, western and southern coasts of the island, mostly in relatively 130

protected bays or straits, but are not found on the more exposed eastern coast, and all are 131

fished though with varying degrees of intensity. 132

Banggai cardinalfish habitat in the endemic distribution within the Banggai 133

Archipelago is limited to shallow coastal waters with a maximum depth of 5-6m, including 134

coral reefs, reef flats, seagrass beds, lagoons and at a few sites Rhizophora sp. prop roots 135

(Vagelli and Erdmann, 2002; Moore et al., 2012). Local extinction or extirpation (as defined 136

by Woodruff, 2001) has been observed, with no recolonisation from populations a few 137

hundred meters away but separated by deeper water (Ndobe et al., 2013). Around Banggai 138

Island the distribution of P. kauderni populations appears to be discontinuous, with no fish 139

observed or reported by fishermen along steeply sloping or more exposed coasts. 140

Combining the geophysical characteristics of the island with the life history traits of P. 141

kauderni, it could be expected that the population structure of P. kauderni around Banggai 142

Island would comprise several reproductively isolated or closed populations (Kritzer and Sale 143

type A) and or one or more metapopulations (Kritzer and Sale type B) with limited 144

connectivity, each of which should be considered as a separate management unit or stock. 145

Indeed Hoffman et al. (2005) and Vagelli et al. (2009) each reported two sites (P. kauderni 146

populations) with significantly different genetic characteristics. The genetic study approach 147

presented in Ndobe et al. (2012) provided further information on 6 sites (Bone Baru where 148

many fish from all over the endemic distribution had been released was purposely excluded), 149

using the same pair of microsatellites (Pka06 and Pka11, Hoffmann et al., 2004) as Vagelli et 150

al., (2009). The results indicated that there were at least 4 closed populations and one 151


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metapopulation, hence from a fisheries management and intra-specific conservation point of 152

view, at least 5 stocks. The endemic distribution of P. kauderni (based on Vagelli, 2008), the 153

sampling sites of all three studies and the suspected breaks due to geophysical characteristics 154

(based on Ndobe et al., 2012) as well as known introduced populations are shown in Fig. 1. 155

156

Sources: Erdman and Vagelli (2001); Vagelli and Erdmann (2002); Moore and Ndobe (2007b); Lilley (2008); 157

Vagelli (2008); Moore et al. (2011); Ndobe et al. (2012); Ndobe and Moore (unpublished data) 158

Figure 1. P. kauderni endemic distribution, known introduced populations, suspected barriers 159

to dispersion, genetic and morphometric sampling sites around Banggai Island 160


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Traders had expressed preference for fish from certain sites, saying that the colours 161

were brighter and more attractive, suggesting there might be external differences between 162

populations and which could be due to genetic, environmental or other factors. Morphometric 163

studies on P. kauderni concluded that there was no significant difference in external 164

morphology between male and female Banggai cardinalfish (Vagelli and Volpedo, 2004; 165

.Ndobe et al., 2013). However no morphometric studies had been published on P. kauderni 166

populations. Furthermore, the relatively recent geometric morphometric approach is widely 167

considered to have greater powers of resolution at an intra-species level than classical 168

morphometrics (Slice, 2007; Madderbacher et al., 2008; Kerschbaumer and Sturmbauer, 169

2011; Klingenberg, 2011) but had not previously been applied to P. kauderni. 170

In this context it was considered important to study and compare the putative P. 171

kauderni stocks around Banggai Island from a morphometric point of view, using classical as 172

well as geometric morphometric methods and to compare the results with genetic and 173

geophysical data, while taking into consideration known fishery/trading history. The results 174

would provide information of use in both management of the ornamental fishery and the 175

process of MPA planning, including zonation. 176

METHODS 177

Populations and Stocks 178

For the purposes of this study, the term population was considered to refer to the Banggai 179

cardinalfish P. kauderni living within a particular geographic area. For example the Palu Bay 180

(introduced) population, the endemic population in the Banggai Archipelago or the Popisi 181

population. A given population should be considered to be a stock if it could be shown to 182

have the characteristics listed by Waldman (2005), and or could be considered a closed 183

population or metapopulation in the sense of Kritzer and Sale (2004). 184

Statistically significant variation in morphometric traits between populations could indicate 185

genetic (reproductive) isolation and consequent divergent evolution due to factors such as the 186

local environment, anthropogenic impacts and stochastic events (separate stocks). Such 187

variation could also reflect adaptation to prevailing conditions at the individual level without 188

necessarily defining separate stocks. Based on the precautionary principle, arguably 189

management should aim to conserve each population exhibiting characteristics indicative of a 190

distinct stock, each of which should be managed separately from a responsible fisheries and 191

conservation viewpoints, unless it could be proven that all or some of the putative stocks 192

were part of a patchy population (sensu Kritzer and Sale, 2004) with significant gene flow 193

and a high likelihood of replenishment of extirpated sub-populations should they occur. 194


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Sample Collection 195

As P. kauderni is not a protected fish species, and the collection areas do not yet have 196

protected area status, no special collection or research permits were necessary. Adult Banggai 197

cardinalfish Pterapogon kauderni (standard length SL ≥ 42 mm) were collected at random 198

from six populations shown in Fig. 1 with a small fyke net called cang used by the local 199

ornamental fishermen. The specimens were preserved in formalin (4% solution) for 12-24 200

hours then placed in 70% alcohol for transportation and storage. The site names, codes, 201

geographical coordinates are listed in Table 1. 202

Table 1. Sample sites, number of specimens and their use 203

Sampling site (village) Coordinates (WGS 84) Number of Specimens

Station Name Codes Latitude Longitude Total GM CM*

Popisi PO - POA S 1º 29' 57" E 123º 30' 54" 33 33 30

Paisulimukon PL - PLN S 1º 33' 36" E 123º 28' 42" 31 31 30

Tinakin Laut TI - TIN S 1º 36' 07" E 123º 29' 24" 33 32 30

Monsongan MO - MON S 1º 37' 54" E 123º 28' 53" 31 31 30

Tolokibit TO - TOL S 1º 42' 46" E 123º 30' 58" 33 33 30

Matanga MA - MAT S 1º 42' 47" E 123º 34' 58" 32 32 30

Total 193 192 180

GM = geometric morphometric study; CM = classical morphometric study 204

* Fin samples were also collected from these 30 samples for genetic analysis 205

Classical Morphometric Methods 206

The classical ichthyological morphometric parameters measured are shown in Fig. 2 along 207

with the codes used and the description of each parameter. 208

209

Figure 2. Classical morphological parameters measured 210


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The parameters were measured using a digital calliper with a precision of ±0.01mm. 211

Ratios of the eleven parameters measured were calculated, producing ten dimensionless 212

parameters. Data on five of these parameters were available from a morphometric study on 213

the P. kauderni Palu Bay introduced population (Ndobe et al., 2013), with the code TP. These 214

data were compared with data from the six Banggai Island sites (Table 1). The dimensionless 215

parameters analysed for the Banggai Island sites and those for which data from Palu Bay 216

were used for comparison are listed in Table 2. 217

Table 2. Dimensionless morphometric parameters tested 218

Ratio Banggai Island

Palu Bay (TP)

Ratio Banggai Island Palu

Bay (TP)

TL/SL 3 sites X DF1/SL X X

HL/SL X X DF2/SL X X

HH/SL X - AF/SL X -

SL/BH (aspect ratio)

X X VF/SL X -

HH/BH X - LJL/SL X -

The data were tabulated and statistical analyses implemented in Microsoft EXCEL 219

2007. The mean (average) and standard deviation were calculated for each parameter (ratio) 220

by site (n = 30) and for the sample as a whole (N = 180). Results were analysed graphically. 221

Analysis of variance (ANOVA) was applied to each ratio for each pair of sites. F values 222

were used to determine the level of significance for each pairwise comparison at 95% and (if 223

appropriate) 99%. The results were analysed to produce matrices of variance between sites. 224

An index of overall morphological variance (Imv) between the populations of each pair of 225

sites was calculated based on the number of ratios with significant or very significant 226

variation between them using the equation: 227

Imv (site i, site j) = nα=0.05 (i,j) + 2 · nα=0.01(i,j) 228

where nα=0.05 (i,j) is the number of parameters (0-10) for which variance between 229

sites i and j is significant at the 95% confidence limit (F > Fcrit (α=0.5)) 230

nα=0.01(i,j) is the number of parameters (0-10) for which variance between 231

sites i and j is significant at the 99% confidence limit (F > Fcrit (α=0.1)) 232

Imv was calculated for all 10 ratios, the 6 body shape ratios and the 4 fin length ratios. 233

The results from these analyses were analysed descriptively, taking into account the various 234

factors likely to be influencing the populations at each site. This analysis produced initial 235

indications regarding population structure and stock boundaries as well as inferences drawn 236

from the morphological characteristics of the introduced and endemic populations. 237


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Geometric Morphometric Methods 238

Software and Digitising 239

The geometric morphometric analysis used the MorphoJ software (Klingenberg, 2011). 240

Each specimen was photographed using a high resolution digital camera with standardised 241

position (pinned to a polystyrene plaque) at a set distance from the camera lens with at least 242

two repeats per specimen. Digitising and conversion to a file format compatible with 243

MorphoJ was accomplished using two utilities: tps.dig and tps.util (Rohlf, 2012). Digitising 244

was done at least twice for each photograph. 245

Landmarks 246

As for any geometric morphometric method, the first requirement was to establish a set 247

of landmark points for the organism to be studied. As there were no previous studies on the 248

Banggai cardinalfish Pterapogon kauderni, landmarks were chosen based on examples from 249

other taxa and salient features of P. kauderni external morphology. The first set of landmarks 250

comprised 17 points, greater than the ideal number of points (≤ 15, i.e. ≤50% of the lowest 251

number of individuals per group). The final 14 landmark set used is shown in Fig. 3. 252

Although contributing to visual representation of the variation in shape between populations 253

by defining the caudal peduncle, trials showed that the elimination of three of the original 17 254

points (between 6 and 7 on lateral line and above and on the outline vertically above and 255

below 14 in Fig.3) did not alter the statistical significance level of the two analyses used. 256

257

Figure 3. Landmark set for Pterapogon kauderni 258


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Identifier Strings and Classifiers 259

In MorphoJ each digitised shape must have a unique identifier string. These strings 260

were created during the digitation process in tps.dig and tps.util. Based on the characters at 261

specific locations in this string, classifiers can be assigned in MorphoJ. The format given to 262

each string and the classifiers defined and used in this study are given in Table 3. 263

Table 3. Identifier strings and classifiers 264

Item

Number and

position (p)

of characters

Value range or

format Definition/Remarks

Classifier string for

each digitised

image input

7

(p: 1 to 7) XXXnnYm

XXX = 3 letter (A-Z)

nn = 2 digit integer

Y = L (left) or R (right) side

m = repeat number (integer < 9)

Classifier "site" 3

(p: 1 to 3) XXX XXX = 3 letter (A-Z) site code

(see Table 1)

Classifier "side" 1

(p: 6 or -2) Y Y = L (left) or R (right) side

Classifier "repeat" 1

(p: 7 or -1) m m = repeat number

(integer from 1 to 3)

Classifier "fish" in

the non-averaged

(input) data set

and

Classifier string for

data set averaged

by "fish"

5

(p: 1 to 5) XXXnn

XXX = 3 letter (A-Z) site code

nn = 2 digit integer, assigned

number of each fish (between 01

and 30 to 34 depending on the

number of specimens sampled

from each site)

265

Procrustes Configuration and Data Validation 266

Shape can be mathematically defined as the entire geometric information about a 267

landmark configuration except its position, orientation, and scale (Dryden & Mardia 1998 in 268

Klingenberg, 2011). Procrustes configuration in MorphoJ was used to eliminate the elements 269

of position, orientation and scale through superimposition, rotation and scaling to unity, thus 270

producing a series of centroids enabling comparison of shape alone. In MorphoJ the scale 271

(size) element is retained in the data set (though not in the centroid itself) and can be used in 272

certain analyses (not presented here) where size can be an important factor, for example as a 273

proxy for ontogenetic differences. However in this study all individuals were within the adult 274

size range and analyses concentrated on centroid shape. 275

The digitised data were examined for outliers. After 4 mis-numbered landmarks were 276

corrected, one specimen (which had appeared abnormal from qualitative observation) 277

remained an extreme outlier, and was not used in further analyses. Repeats for each specimen 278


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(photographs and digitising) were checked for consistency using the Procrustes ANOVA 279

function, to ensure that measurement error was not significant compared to the variation 280

between individuals. Once these steps were completed, the repeats for each individual were 281

merged to produce a data set of centroids representing the 192 individuals from the 6 sites (P. 282

kauderni populations) listed in Table 1. 283

Canonical Variate Analysis (CVA) 284

Canonical variate analysis (CVA) is a type of ordination analysis, which maximizes the 285

separation of specified groups (Klingenberg, 2011). This analysis can be applied to several 286

populations at once and was run for the whole data set with "site" as the classifier variable. 287

The number of canonical variates is one less than the number of groups, and with six 288

populations was therefore five. Outputs included statistical analyses with estimates of the 289

significance (P values) and extent (Procrustes Distance) of between population (site) 290

morphometric variation; graphic representations of the deformation function between the 291

average shape of the whole sample (N = 192) and the average shape of each population; and 292

plots of the spread of the specimens on axes representing any two of the canonical variates, 293

essentially projecting two dimensions of the multi-dimensional shape space onto the X and Y 294

axes. Between group (population) shape differences were considered significant if P ≤0.05 295

and highly significant if P < 0.0001. 296

Discriminant Function Analysis (DFA) 297

The discriminant function analysis (CVA) with cross-validation indicates whether 298

groups can be distinguished reliably (Klingenberg, 2011). This analysis can only be 299

performed on two groups at one time and was run for each possible pairwise combination of 300

sites. The discriminant function produced was validated using 1000 random permutations. 301

Outputs included Procrustes distance, significance (parametric P value and P value for 1000 302

permutations), accuracy of the DFA in separating the original data (% separated) and in 303

assigning each specimen correctly under 1000 random permutations (% correctly assigned). 304

Pairwise shape differences between populations represented by the discriminant function 305

were considered significant if P ≤ 0.05 and highly significant if P < 0.0001. 306

Synthesis 307

The results of the classical and geometric morphometric analyses were compared with each 308

other and with the results of the genetic study described in Ndobe et al. (2012). The 309

combined results were reviewed in the context of geophysical, ecological and socio-economic 310

conditions including the ornamental fishery with respect to population structure, stock 311

boundaries, management implications and future research needs. 312


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RESULTS AND DISCUSSION 313

Classical Morphometric Results 314

The average values for each population of each of the 10 ratios are shown in bar graph form 315

with standard error bars in Fig 4. The significance levels for each site pair for each of the 10 316

ratios are shown in Table 3, salient points are indicated in foot notes beneath the relevant 317

graphs. The index of morphometric variance Imv values are shown in Table 4. 318

319

320

Popisi: shorter head length; Matanga and Tolokibit; lower (more pointed) head shape 321

322

Indication of radiation of increasing aspect ratio from Tinakin Laut (TI) 323


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324

Heads more tapered in Tinakin, Tolokibit and Matanga 325

326

Shorter lower jaw length in Popisi consonant with shorter (and higher) head 327

328

329

Both dorsal fins shortest in Tolokibit and longest in Tinakin Laut 330


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331

332

Similar variation in anal and ventral fins, shortest in Tolokibit, longest in Tinakin Laut 333

334

Tails longest in Matanga, shortest in Tolokibit, average in Popisi and Palu Bay 335

Figure 4. Ten morphometric ratios: average values per site ± SD 336

The data in Fig.4. show some specific characteristics for each population. Shorter fins 337

in Tolokibit, longer fins in Tinakin Laut and Monsongan; a relatively elongated, streamlined 338

shape in Matanga; short blocky heads in Popisi; and relatively large heads with relatively 339

short fins in Paisulimukon. The Palu Bay population, founded through the release of fish 340

from several populations including Tolokibit, was close to the total sample average for three 341

head/body shape ratios, but had relatively short dorsal fins, possibly connected to this origin. 342

343 PeerJ PrePrints | http://dx.doi.org/10.7287/peerj.preprints.182v1 | CC-BY 3.0 Open Access | received: 30 Dec 2013, published: 30 Dec 2013

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Table 3. Pairwise ANOVA results for 10 Ratios and 6 sites 344

1. TL/SL Fcrit α=0.05 = 4.043; Fcrit α=0.01 = 7.194; N = 75; n = 25

Paisulimukon Tinakin Monsongan Tolokibit Matanga

Popisi * **

Paisulimukon

Tinakin

Monsongan

Tolokibit **

Fcrit α=0.05 = 4.007; Fcrit α=0.01 = 7.093; N = 180; n = 30

2. HH/SL Paisulimukon Tinakin Monsongan Tolokibit Matanga

Popisi ns ns ns ** **

Paisulimukon * ns ** **

Tinakin ns * *

Monsongan ** **

Tolokibit ns

3. BH/SL Paisulimukon Tinakin Monsongan Tolokibit Matanga

Popisi ns ns ** ** **

Paisulimukon ns ns ** **

Tinakin ns ** **

Monsongan ** **

Tolokibit ns

4. HL/SL Paisulimukon Tinakin Monsongan Tolokibit Matanga

Popisi ns ns ** ** **

Paisulimukon ns * * **

Tinakin ns ns ns

Monsongan ns ns

Tolokibit ns

5. LJL/SL Paisulimukon Tinakin Monsongan Tolokibit Matanga

Popisi ** ** ** ns *

Paisulimukon ns ns * ns

Tinakin ns ns ns

Monsongan * ns

Tolokibit ns

6.HH/BH Paisulimukon Tinakin Monsongan Tolokibit Matanga

Popisi * ** * ** **

Paisulimukon * ns * ns

Tinakin ns ns ns

Monsongan ns ns

Tolokibit ns

345


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7. AF/SL Paisulimukon Tinakin Monsongan Tolokibit Matanga

Popisi ns * ** * **

Paisulimukon ** ** ns **

Tinakin ns ** ns

Monsongan ** ns

Tolokibit **

8. VF/SL Paisulimukon Tinakin Monsongan Tolokibit Matanga

Popisi ns ** ** ** *

Paisulimukon ** * ns ns

Tinakin * ** **

Monsongan ** *

Tolokibit *

9. DF1/SL Paisulimukon Tinakin Monsongan Tolokibit Matanga

Popisi ns ** * ns **

Paisulimukon ** ** ns **

Tinakin ns ** ns

Monsongan ** *

Tolokibit **

10. DF2/SL Paisulimukon Tinakin Monsongan Tolokibit Matanga

Popisi ns ns ns ** ns

Paisulimukon ns ns ** ns

Tinakin ns ** ns

Monsongan ** ns

Tolokibit **

N = total number of specimens in analysis; n = number of specimens per site 346

Table 4. Morphometric Variation Index Imv for 6 sites 347

All 10 ratios Paisulimukon Tinakin Monsongan Tolokibit Matanga

Popisi 3 9 12 14 16

Paisulimukon 8 6 10 10

Tinakin 1 11 5

Monsongan 13 6

Tolokibit 9

Body shape Paisulimukon Tinakin Monsongan Tolokibit Matanga

Popisi 3 4 7 9 11


Tinakin 0 3 3

Monsongan 5 4

Tolokibit 2

Fin length Paisulimukon Tinakin Monsongan Tolokibit Matanga

Popisi 0 5 5 5 5


Tinakin 1 8 1

Monsongan 8 2

Tolokibit 5 PeerJ PrePrints | http://dx.doi.org/10.7287/peerj.preprints.182v1 | CC-BY 3.0 Open Access | received: 30 Dec 2013, published: 30 Dec 2013

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The classical morphometric data show very little difference between the Tinakin Laut 348

and Monsongan populations with only one significant ratio, the relative length of the ventral 349

fin (VF/SL). These two populations also have the highest within site variability for several 350

parameters. Although the distance between these two sites in terms of coastline length is 351

similar to that between several other pairs, and the shallow water environment is somewhat 352

different, there is no obvious break in P. kauderni habitat between these two sites with reef 353

flats of varying width extending along the intervening coast. Despite the extreme philopatry 354

exhibited by P. kauderni based on behavioural and genetic studies (Kolm et al., 2005) and 355

inferred from genetic population data (Vagelli et al., 2009), it is likely that some natural 356

migration and therefore genetic exchange does take place. 357

Furthermore, intermixing between these two sites could have been facilitated by the 358

prevalent fishing and trading patterns in the late 1990's to around 2004. In Bone Baru where 359

the ornamental fishermen have tended to exploit a large number of fishing grounds, so that 360

fish from many sites have been released in substantial numbers. However when the trade was 361

active in these two villages, the Monsongan and Tinakin Laut ornamental fishers tended to 362

catch most fish in or close to their own village however it is possible that there have been 363

unsold fish from other sites released, especially from Tinakin Laut and possibly Tolokibit at 364

Monsongan and from Monsongan and possibly Paisulimukon at Tinakin Laut. 365

The greatest difference is between the populations at the two extremities of the Banggai 366

cardinalfish distribution, Popisi in the north and Matanga in the southeast. This could be 367

related to distance, a hypothesis for which the matrices in Table 4 show some support, with 368

either a latitudinal gradient or radiation from the Tinakin Laut/Monsongan area. 369

Alternatively, habitat could be a factor. Popisi is the most sheltered of the six sites, while 370

Matanga is the most exposed. The relatively hydrodynamic body and long fins of the 371

Matanga population could be an adaptation by natural selection on genetic traits or influence 372

on individual growth. Conversely the relatively large chunky head shape exhibited by the 373

Popisi population would not be a disadvantage in the calm waters of the bay and might 374

provide other advantages such as greater capacity for mouthbrooding. 375

Several ratios are significant to a level between 90% and 95%, in particular between 376

Popisi and Paisulimukon. While not considered statistically significant, biological and 377

ecologically these differences could be of significance and indicate that the two populations 378

are more distinct morphometrically than might appear from Table 3 and Table 4. 379

Overall, the classical morphometric data indicate five possible stocks: Popisi, 380

Paisulimukon, Tinakin/Monsongan, Tolokibit and Matanga. The comparison with the Palu 381


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Bay population reinforces the possibility of mixed origins in the founder population. Despite 382

the statistical significance of variation in some of the morphometric ratios at a population 383

level, the level of overlap between individuals from different sites means that none of these 384

ratios can be used as a marker to identify the origin of a particular individual, such as the 385

lower jaw length and dorsal fin which enabled Uglem et al. (2011) to distinguish (with a 386

confidence level in excess of 95%) between wild cod (Gadus morhua) and escapees from 387

aquaculture facilities. 388

Geometric Morphometrics 389

Canonical Variate Analysis (CVA) 390

The eigenvalues and variance explained by each of the five canonical variates are shown in 391

Table 5. These values indicate that the first canonical variate (CV1) explains over half of the 392

total variance and the first three variates explain almost 90% of total variance. 393

Table 5. Canonical variate eigenvalues and proportion of variance explained 394

Graphic representations of the first three canonical variates are shown in Fig. 5. The 395

points show the average position (for all 192 specimens) of each landmark, and the lines 396

represent the direction and relative magnitude of the deformation from this average shape 397

represented by the canonical variate. The canonical variates CV1 and CV3 both seem to 398

relate quite strongly to aspect ratio while CV2 seems more related to head shape. 399

Plots of the 192 individuals with 90% confidence ellipses of the six sites (populations) 400

for two dimensional plots with X or Y axes of CV1, CV2 and CV3 are shown in Fig 6. CV5 401

and CV5 (not shown) did not show any significant separation between sites and seem to 402

relate to individual rather than population or site-based characters. 403

The value of P < 0.0001 for the between site analysis of variance (ANOVA) for the 404

total sample (N = 192) shows that there is significant variance between populations based on 405

the canonical variates. The pairwise between site P values are shown in Table 6, and show 406

significant Procrustes distance between all site pairs except Tinakin Laut and Monsongan 407

(TIN-MON). 408

Canonical Variate

(CV) Number Eigenvalue

% of variance

explained

Cumulative % of

variance explained

1 3.11095 57.088 57.088

2 1.0215 18.745 75.833

3 0.76136 13.972 89.805

4 0.30743 5.642 95.446

5 0.24816 4.554 100


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409

410

411

Figure 5. Deformation grid and direction of deformation from average shape represented 412

by the first three canonical variates (CV1, CV2, CV3) 413


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414

415

416

Figure 6. Distribution of the six study sites on the three first canonical variate axes: 417

CV1/CV2 (top), CV1/CV3 (centre) and CV2/CV3 (bottom) 418


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419

Table 6. Significance of between site Procrustes Distance 420

Pairwise P values (below diagonal) and significance level (above diagonal)

POA PLN TIN MON TOL MAT

POA

** ** ** ** **

PLN <0.0001

* ns# * **

TIN <0.0001 0.0043

ns * **

MON <0.0001 0.0619 0.2067

* *

TOL <0.0001 0.0007 0.0015 0.0324

*

MAT <0.0001 <0.0001 <0.0001 0.0023 0.0228

* significant; ** highly significant; ns non statistically significant; # P ≤ 0.07, in the range 421

sometimes considered significant in biological or ecological terms (Klingenberg, 2012) 422

The plots in Fig. 6 show that Matanga and to a lesser extent Tolokibit each exhibit 423

considerable difference from the other 4 sites and from each other with respect to CV1. With 424

respect to CV2, there are three groups: Popisi is markedly different from the Monsongan-425

Tinakin sites which almost wholly overlap while the other three sites (Paisulimukon, 426

Tolokibit and Matanga) show substantial overlap. The CV3 axes show Paisulimukon as being 427

well separated from the other 5 sites. Together the plots show that the only two sites not 428

markedly separated from all other sites on any of the three axes are Tinakin Laut and 429

Monsongan. 430

Discriminant Function Analysis (DFA) 431

Unlike the canonical variate analysis (CVA), the discriminant function analysis (DFA) in 432

MorphoJ can only be run for two groups, in this case for the 15 possible site pairs. The results 433

of the parametric analysis which sets up the discriminant function (DF) and of the validation 434

assignment tests of each DF (with 1000 random permutations) are shown in Table 7. 435

Examples of the deformation or transformation represented by the DF are shown in Fig. 7. 436

Examples of the distribution of the individuals within each population relative to the 437

discriminant function are shown in Fig. 8. Examples of the results of the DF validation 438

assignment tests are shown in Fig. 9. 439

The data in Table 7 show that all site (population pairs are significantly different under 440

the parametric discriminant function produced, with 95% to 100% of fish being described as 441

belonging to the correct site. The level (%) of successful attribution under the validation test 442

varied, but was statistically significant for 5 site pairs and highly significant for 9 site pairs. 443

The highest validation score (98%) was for Popisi-Matanga, while Monsongan-Tolokibit had 444

the lowest significant validation score (72%). However one site pair, Tinakin Laut-445

Monsongan, was not significantly discriminated under the validation test. 446


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447

Table 7. Pairwise DFA analysis significance, discrimination and validation 448

Site

(Population)

P value and significance Discriminant

power of the

DF (%)

Correct

validation

assignment (%) Parametric

(DF)

Validation

(1000 random

permutations)

POA-MAT <0.0001 ** <0.0001 ** 100 98

POA-TOL <0.0001 ** <0.0001 ** 100 94

POA-MON <0.0001 ** <0.0001 ** 100 87

POA-TIN <0.0001 ** <0.0001 ** 95 76

POA-PLN <0.0001 ** <0.0001 ** 98 78

PLN-MAT <0.0001 ** <0.0001 ** 100 87

PLN-TOL <0.0001 ** <0.0001 ** 95 80

PLN-MON <0.0001 ** 0.0010* 100 89

PLN-TIN <0.0001 ** <0.0001 ** 97 86

TIN-MAT <0.0001 ** <0.0001 ** 100 95

TIN-TOL <0.0001 ** 0.0010* 100 95

TIN-MON <0.0001 ** 0.0840 ns

97 87

MON-MAT <0.0001 ** 0.0020* 100 92

MON-TOL <0.0001 ** 0.0380* 97 72

TOL-MAT <0.0001 ** 0.0230* 100 76

** = highly significant; * significant; ns

not statistically significant 449

450

451


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452

Figure 7. Graphical representation of the distortion represented by the Discriminant Function 453

(DF) for 3 study site pairs: MAT-POA; PLN-TOL; MAT-TOL (with x 6 magnification) 454

455

456

457

Figure 8. Descriminant Function (DF) score distribution 3 site pairs: 458

MAT-POA (top); PLN-TOL (centre) ; MON-TIN (bottom) 459


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460

461

462

Figure 9. Discriminant Function (DF) cross-validation scores for 3 site pairs: 463

MAT-POA (top); PLN-TOL (centre); MON-TIN (bottom) 464

Synthesis – morphometric and other data 465

The two morphometric methods used provide different and complimentary information on 466

population characteristics, but both produce the same result in terms of stock identification, 467

pointing to 5 stocks, four of which are likely to be closed or very nearly closed populations 468

(Matanga, Tolokibit, Paisulimukon and Popisi) and one of which would seem to display the 469

characteristics of a metapopulation (Tinakin Laut-Monsongan). This result fits in well with 470

geophysical data on potential breaks in habitat (Ndobe et al., 2012), and genetic data from 471

Hoffman et al. (2005) and Vagelli et al. (2009) and reinforces the conclusion drawn from 472


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genetic analysis on the same sites and sample specimens (S. Ndobe, unpublished). A map of 473

the proposed P. kauderni stock boundaries around Banggai Island is shown in Fig. 10. 474

475

Figure 10. Five proposed P. kauderni stocks around Banggai Island 476

Many factors or processes could contribute to or cause the observed differences 477

between populations and the evolution of the proposed stocks. One possibility could be 478

radiation for example if a founder population had been established and then slowly spread 479

(N-S or S-N or N and S from an intermediary point) at a period when sea levels were lower 480

and current habit was connected by shallow coastal habitat corridors. The populations might 481

then have become separated and evolved differently when sea levels rose. Such an 482

explanation for population structure has been proposed for other fishes, for example the 483

striped snakehead Channa striata (Jamaluddin et al., 2011). 484

It is possible and even likely that trade has resulted in some anthropogenic movement 485

of individuals from one site (and possibly population or stock) to another, mainly from 486

Banggai or Bandang Islands as previously mentioned. Between site environmental 487

differences may have driven site-specific selection and evolution, for example exposure to 488

waves and currents, habitat typology and microhabitat availability. For example the relatively 489

elongated form and long tails/fins in Matanga may be an adaptation to the exposed nature of 490


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the site. In the east monsoon powerful waves and strong currents tend to reduce the P. 491

kauderni population in most years, so that a better swimming ability would be an 492

advantageous trait likely to increase survival and reproductive success, despite possible trade-493

off such as reduced ability to store energy for mouthbrooding or potentially reduced volume 494

of the buccal cavity and hence brooding capacity of males. 495

Another theoretical possibility is that of remnant populations or stocks. The Banggai 496

Archipelago was originally a fragment from the Australasian tectonic plate which moved 497

north. It is possible, even probable that P. kauderni evolved and spread across this plate, 498

much of which would have been shallow seas suitable as habitat. Rising sea levels could have 499

reduced this widespread population with at least some genetic connectivity to a number of 500

relatively small and increasingly isolated sub-populations or stocks well before historical 501

times. Extirpations and subsequent recolonising radiations could have occurred. 502

Further research might be able to elucidate the biogeography and genetic population 503

structure as well as morphometric characteristics of P. kauderni. For example, 504

multidisciplinary evolutionary studies of the area; genetic research on the phylogeny and 505

ancestral origins of P. kauderni; genetic populations studies using more than two 506

microsatellites or other genetic methods (e.g. sequencing); studies of other morphometric and 507

meristic characters including colour and patterns, which appear to vary between at least some 508

sites; in-depth long-term studies on reproductive success, recruitment and individual 509

movement patterns; and combined morphometric and genetic studies in other areas of the P. 510

kauderni distribution. 511

Based on the precautionary approach to fisheries resource management now widely 512

advocated, the data already available provide a basis for managing the ornamental fishery in 513

the waters around Banggai Island and to inform the zonation of Banggai Island for P. 514

kauderni conservation in the context of the District MPA. Indeed zonation options based on 515

this and other research have been produced (Ndobe, unpublished) using the MARXAN MPA 516

planning software (Ball and Possingham, 2000). 517

Despite already having an (untenanted) office in Bone Baru since 2009, the Banggai 518

Kepulauan District MPA was still in the planning stage in early 2013 when the District was 519

further subdivided. The new Banggai Laut District with the town of Banggai on Banggai 520

Island as its capital, comprises the majority of the P. kauderni endemic distribution in the 521

southern part of the archipelago. Clearly the District MPA will have to be reviewed. Options 522

include establishing two District MPAs, a cross-boundary MPA under higher level 523

jurisdiction (provincial or national), or abandonment. Either of the first two options would 524


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provide an opportunity to improve the effectiveness of the original design, which was poor 525

from several aspects and in particular from a P. kauderni conservation point of view (Ndobe 526

et al., 2012). 527

CONCLUSION 528

Both morphometric methods used show significant differences between the six P. kauderni 529

populations studied. The population structure indicated conforms with genetic study results, 530

and strongly indicate the presence of 5 stocks in the waters around Banggai Island. We 531

propose that these stocks should be treated as management units and thus as a basis for P. 532

kauderni management in the context of the ornamental fishery and in conservation 533

management, in particular the process of reviewing and implementing the District MPA. 534

We recommend further research to improve understanding of the phenomena causing 535

the observed differences, as well as similar studies (ideally combining genetic and 536

morphometric analyses) in other sites across the P. kauderni distribution. We consider that 537

application of morphometric geometrics would be beneficial in other aspects of P. kauderni 538

bioecology, for example seeking means of differentiating female and (non-brooding) male 539

Banggai cardinalfish as well as applications to other species in Indonesia, where the method 540

is still little known. 541

ACKNOWLEDGMENTS 542

The authors wish to thank all who in any way supported the research and the writing of this 543

article. We are aware that this first version, and could be significantly improved. We 544

welcome and express our gratitude in advance to all who may offer constructive criticism and 545

advice on this pre-print article, which we hope to publish with PeerJ as a peer reviewed 546

research article. 547

REFERENCES 548

Adams C.E., Fraser D., Wilson A.J., Alexander G., Ferguson M.M., Skulason S. (2007).

Patterns of phenotypic and genetic variability show hidden diversity in Scottish

Arctic charr. Ecology of Freshwater Fish 16: 78–86.

Allen G.R. (2000). Threatened fishes of the world: Pterapogon kauderni Koumans, 1933

(Apogonidae). Environmental Biology of Fishes 57 : 142

Allen G.R. and Donaldson T.J. (2007). Pterapogon kauderni. In: IUCN 2009. IUCN Red

List of Threatened Species. Version 2009.1. <www.iucnredlist.org>. [Download 22

Agustus 2009]

Beg G.A and Waldman J.R. (1999). An holistic approach to fish stock identfication.

Fisheries Research 43 (35): 44.


PrePrin

ts

29

Bernardi G. and Vagelli A. (2004). Population structure in Banggai cardinalfish,

Pterapogon kauderni, a coral reef species lacking a pelagic larval phase. Marine

Biology 145 : 803–810

Bruins E.B.A., Moreau M.A., Lunn K.E., Vagelli A.A. and Hall H. (2004). 10 Years after

rediscovering the Banggai Cardinalfish. Musée Océanographique, Monaco. Bulletin

de l'Institut Océanographique 2004, 77 (1446) : 71-81

Burridge A.K. (2012). A short introduction to using TpsUtil, TpsDig2 and TpsRelw

developed by F. James Rohlf ([email protected]). Naturalis Biodiversity

Center. http://www.science.naturalis.nl/burridge [downloaded 14 December 2012]

Cabral H.N., Marques J.F., Rego A.L., Catarino A.I., Figueiredo J and Garcia J. (2003).

Genetic and morphological variation of Synaptura lusitanica Capello, 1868, along

the Portuguese coast. Journal of Sea Research 50: 167– 175

Coyle T. (1998). Stock identification and fisheries management: the importance of using

several methods in a stock identification study. pp 173-172 in Hancock D.A. (ed).

(1998). Taking stock: defining and managing shared resources, Australian Society

for Fish Biology, Sudney, Australia. [asfb.org.au/pdf/1997/1997-04-04b.pdf ]

Erdmann M.V. and Vagelli A.A. (2001). Banggai Cardinalfish Invade Lembeh Strait. Coral

Reefs 20 : 252-253.

Froese R. and Pauly D. Editors. (2011). FishBase. World Wide Web electronic publication.

http:www.fishbase.org/summary/Pterapogon-kauderni.html [accessed on 4th

November 2012]

Hammer C. and Zimmermann C. (2005). The Role of Stock Identification in Formulating

Fishery Management Advice. In: Cadrin, S.X., Friedland, K.D.,Waldman, J.R.

(Eds.), Stock Identification Methods. Elsevier Academic Press, Burlington, MA, pp.

631-658

Hoffman E.A., Arguello J.R., Kolm N., Berglund A. and Jones A.G. (2004). Eleven

polymorphic microsatellite loci in a coral reef fish, Pterapogon kauderni. Molecular

Ecology Notes 4 : 342-344

Hoffman E.A., Kolm N., Berglund A., Arguello J.R. and Jones A.G. (2005). Genetic

structure in the coral-reef-associated Banggai cardinalfish, Pterapogon kauderni.

Molecular Ecology 14 : 1367–1375.

Hossain M.A.R., Nahiduzzaman M., Saha D., Khanam M.U.H, and Alam M.S. (2010).

Landmark-Based Morphometric and Meristic Variations of the Endangered Carp,

Kalibaus Labeo calbasu, from Stocks of Two Isolated Rivers, the Jamuna and Halda,

and a Hatchery. Zoological Studies 49(4): 556-563

Indrawan M. and Suseno (2008). The complications of CITES inclusion of endemic species

in Indonesia: Lessons learned from an in-country deliberation on protecting the

Banggai cardinalfish, Pterapogon kauderni. SPC Live Reef Fish Information

Bulletin 18 : 13-16

Kerschbaumer M. and Sturmbauer C. (2011). The Utility of Geometric Morphometrics to

Elucidate Pathways of Cichlid Fish Evolution. International Journal of Evolutionary

Biology Volume 2011, Article ID 290245, 8 pages. doi:10.4061/2011/290245

Klingenberg C.P. (2011). MORPHOJ: an integrated software package for geometric

morphometrics. Molecular Ecology Resources 11 : 353–357


PrePrin

ts

30

Kolm N. and Berglund A. (2003). Wild Populations of a Reef Fish Suffer from "Non-

Destructive" Aquarium Trade Fishery. Conservation Biology, 17 (3) : 910-914.

Kolm N., Hoffman E.A., Olsson J., Berglund A., dan Jones A.G. (2005). Group stability

and homing behavior but no kin group structures in a coral reef fish. Behavioral

Ecology 16 : 521–527

Koumans F.P. (1933). On a new genus and species of Apogonidae. Zoologische

Mededeelingen (Leiden), 16 (1-2) : 78, Pl. 1

Kritzer J.P dan Sale P.F. (2004). Metapopulation ecology in the sea: from Levins’ model

tomarine ecology and fisheries science. Fish and Fisheries 5 : 131–140

Lilley R. (2008). The Banggai cardinalfish: An overview of conservation challenges. SPC

Live Reef Fish Information Bulletin, 18 : 3-12

Lunn K.E. and Moreau A.M. (2004). Unmonitored trade in Marine Ornamental Fishes: the

Case of Indonesia's Banggai Cardinalfish (Pterapogon kauderni). Coral Reefs, 23 :

344-341.

Maderbacher M., Bauer C., Herler J., Postl L. Makasa L. and Sturmbauer C. (2008).

Assessment of traditional versus geometric morphometrics for discriminating

populations of the Tropheus moorii species complex (Teleostei: Cichlidae), a Lake

Tanganyika model for allopatric speciation. J Zool Syst Evol Res doi:

10.1111/j.1439-0469.2007.00447.x

Moore A. and Ndobe S. (2007a). The Banggai Cardinalfish and CITES – a local

perspective. Reef Encounters, 38 : 15-17.

Moore A. and Ndobe S. (2007b). Discovery of an introduced Banggai Cardinalfish

population in Palu Bay, Central Sulawesi, Indonesia. Coral Reefs 26 : 569.

Moore A., Ndobe S., Salanggon A.I.M., Ederyan and Rahman A. (2012). Banggai

Cardinalfish Ornamental Fishery: The Importance of Microhabitat. Proceedings of

the 12th International Coral Reef Symposium, Cairns, Australia, 9-13 July 2012.

http://www.icrs2012.com/proceedings/manuscripts/ICRS2012_13C_1.pdf

Ndobe S., Madinawati dan Moore A. (2008). Pengkajian Ontogenetic Shift pada Ikan

Endemik Pterapogon kauderni. Jurnal Mitra Bahari 2 (2) : 32-55

Ndobe S., Setyohadi D., Herawati E.Y., Soemarno and Moore A. (2012). An Ecological

and Social Approach to Banggai Cardinalfish Conservation Management.

Proceedings of the 12th International Coral Reef Symposium, Cairns, Australia, 9-13

July 2012. 17A Science to support the coral triangle initiative.

http://www.icrs2012.com/proceedings/manuscripts/ICRS2012_17A_2.pdf

Ndobe. S., D. Setyohadi, E.Y. Herawati, Soemarno, A. Moore, M.D. Palomares and D.

Pauly. (2013). Life History of Banggai Cardinalfish (Pterapogon kauderni; Pisces,

Apogonidae) from Banggai Islands and Palu Bay, Sulawesi, Indonesia. Acta

Ichthyologica Et Piscatoria, 43 (3): 237–250. DOI: 10.3750/AIP2013.43.3.08

Reiss H., Hoarau G., Dickey-Collas M. and Wolff W.J. (2009). Genetic population

structure of marine fish: mismatch between biological and fisheries management

units. Fish and Fisheries, 10: 361–395. DOI: 10.1111/j.1467-2979.2008.00324.x

Rocha L.A., Craig M.T. and Bowen B.W. (2007). Phylogeography and the conservation of

coral reef fishes. Coral Reefs, DOI 10.1007/s00338-007-0261-7


PrePrin

ts

31

Rohlf F.J. (2012). http://life.bio.sunysb.edu/morph/

Slice D.E. (2007). Geometric Morphometrics. Annual Review of Anthropology, 36: 261–

81, doi : 10.1146/annurev.anthro.34.081804.120613

Turan C. (2004). Stock identification of Mediterranean horse mackerel (Trachurus

mediterraneus) using morphometric and meristic characters. ICES Journal of Marine

Science 61: 774-781. Doi:10.1016/j.icesjms.2004.05.001

Turan C. and Yaglioglu, D. (2010). Population identification of common cuttlefish (Sepia

officinalis) inferred from genetic, morphometric and cuttlebone chemistry data in the

NE Mediterranean Sea. Scientia Marina 74(1) : 77-86

Vagelli A. (1999). The Reproductive biology and early ontogeny of the mouthbreeding

Banggai Cardinalfish, Pterapogon kauderni (Perciformes, Apogonidae).

Environmental Biology of Fishes 56 : 79-92

Vagelli A. (2004). Ontogenetic Shift in Habitat Preference by Pterapogon kauderni, a

Shallow Water Coral reef Apogonid with Direct Development. Copeia 2004(2) :

364-369.

Vagelli A. and Volpedo A.V. (2004). Reproductive Ecology of Pterapogon kauderni, an

endemic apogonid from Indonesia with direct development. Environmental Biology

of Fishes 70 : 235-245

Vagelli A.A. (2008). The unfortunate journey of Pterapogon kauderni: A remarkable

apogonid endangered by the international ornamental fish trade, and its case in

CITES. SPC Live Reef Fish Information Bulletin 18 : 17-28

Vagelli A.A. and Erdmann M.V. (2002). First Comprehensive Survey of the Banggai

Cardinalfish, Pterapogon kauderni. Environmental Biology of Fishes 63 : 1-8

Vagelli A.A., Burford M. and Bernardi G. (2009). Fine scale dispersal in Banggai

Cardinalfish, Pterapogon kauderni, a coral reef species lacking a pelagic larval

phase. Marine Genomics 1 : 129–134.

Vasconcellos A.V., Vianna P., Paiva P.C., Schama R. and Solé-Cava A. (2008). Genetic

and morphometric differences between yellowtail snapper (Ocyurus chrysurus,

Lutjanidae) populations of the tropical West Atlantic Genetics and Molecular

Biology, 31 (1S) : 308-316

Waldman J.R. (2005). Definition of stocks: an evolving concept. In: Cadrin, S.X.,

Friedland, K.D.,Waldman, J.R. (Eds.), Stock Identification Methods. Elsevier

Academic Press, Burlington, MA, pp. 7–16.

Ward R.D. (2006). The importance of identifying spatial population structure in restocking

and stock enhancement programmes. Fisheries Research 80 : 9–18

Woodruff D.S. (2001). Populations, Species and Conservation Genetics. Pp. 811-829 in

Encyclopaedia for Biodiversity Volume 4, Academic Press, San Diego, USA.

549


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